class_docstr: Concept Activation Vector (CAV) is a vector orthogonal to the decision
  boundary of a classifier which distinguishes between activation
  vectors produced by different concepts.
  More details can be found in the paper:
      https://arxiv.org/abs/1711.11279
docstr: Saves a dictionary of the CAV computed values into a pickle file in the
  location returned by the "assemble_save_path" static methods. The
  dictionary contains the concept names list, the layer name for which
  the activations are computed for, the stats dictionary which contains
  information about the classifier train/eval statistics such as the
  weights and training accuracies. Ex.:
  
  save_dict = {
      "concept_ids": [0, 1, 2],
      "concept_names": ["striped", "random_0", "random_1"],
      "layer": "inception4c",
      "stats": {"weights": weights, "classes": classes, "accs": accs}
  }
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code: def save(self):
      r"""
      Saves a dictionary of the CAV computed values into a pickle file in the
      location returned by the "assemble_save_path" static methods. The
      dictionary contains the concept names list, the layer name for which
      the activations are computed for, the stats dictionary which contains
      information about the classifier train/eval statistics such as the
      weights and training accuracies. Ex.:
  
      save_dict = {
          "concept_ids": [0, 1, 2],
          "concept_names": ["striped", "random_0", "random_1"],
          "layer": "inception4c",
          "stats": {"weights": weights, "classes": classes, "accs": accs}
      }
  
      """
  
      save_dict = {
          "concept_ids": [c.id for c in self.concepts],
          "concept_names": [c.name for c in self.concepts],
          "layer": self.layer,
          "stats": self.stats,
      }
  
      cavs_path = CAV.assemble_save_path(
          self.save_path, self.model_id, self.concepts, self.layer
      )
      torch.save(save_dict, cavs_path)
  
file_path: captum/captum/concept/_core/cav.py
imports: import os
  from typing import Any, Dict, List
  import torch
  from captum.concept._core.concept import Concept
  from captum.concept._utils.common import concepts_to_str
label_desc: Use image node_id 3 for calling the CAV obj's underlying member method code with example usage: obj.save() without return types